Collaborative Research: NCS-FO: Intelligent Closed-Loop Neural Interface System for Studying Mechanisms of Somatosensory Feedback in Control of Functional and Stable Locomotion

Sensory feedback from moving legs is critical for functional and dynamically stable locomotion. Although it is clear that motion-related sensory feedback influences inter-leg coordination and selection of gaits (walking, trotting, galloping, etc.), it is not known which sensory modalities (e.g., muscle length- or force-related signals) and sources of feedback (e.g., hip or knee muscles) mediate these locomotor changes. Therefore, this project aims to understand how sensory neurons providing information about the length of hip muscles regulate interlimb coordination and gait selection. This goal will be accomplished by selectively and reversibly stimulating these sensory neurons in an intelligent, closed-loop, and well-controlled manner. This project will lead to the development of new neural implant tools and associated computational algorithms for an in-vivo manipulation of motion-related sensory signals in a large animal model, the cat. The new findings of this project and the developed methods will substantially enhance our understanding of the mechanisms of sensory locomotor control and contribute to developing novel therapeutic interventions. The proposed multidisciplinary research approaches will also significantly expand the utility and capabilities of the rapidly growing field of optogenetics, enabling transformative research and providing unprecedented new experimental tools for neuroscience. The most noticeable long-term benefits of this work to society will be an improvement in the quality of life for a sizable population of people affected by a wide range of movement deficits, from limb loss to sensory neuropathy. These individuals will benefit from the development of neural interfaces between the nervous and engineering systems controlled by machine learning algorithms. Throughout this project, efforts will be made to recruit and train graduate and undergraduate students from underrepresented groups. Outreach activities will also be organized to share resources, tools, and knowledge with teachers, students, and underrepresented groups. The results of the proposed research and educational activities will be shared with students, scientific communities, and the public through science fairs, publications, workshops, conferences, and the Internet.

The overall goal of this proposal is to characterize the mechanisms of somatosensory control of interlimb coordination and gait selection by spindle afferents of hip muscles in the cat model by developing and utilizing in-vivo an intelligent and closed-loop optoelectronic neural interface system. In particular, in this proposal high-density, efficient, and wirelessly-powered implantable opto-electro (WIOE) neural interface devices will be developed. Each WIOE heterogeneously incorporates an optoelectronic array of 64 transparent microelectrodes and 16 microscale light-emitting-diodes (µLEDs), a system-on-a-chip (SoC), and a power receiver (Rx) coil in an mm3-size package, capable of optogenetic stimulation and electrical recording of neural activities. Wireless telemetry links will be implemented for efficient transcutaneous power and wideband data transmission between an external data-acquisition/control unit and the distributed array of WIOE implants. Multiple WIOE devices will be implanted in selected dorsal root ganglia (DRG) of the cat. Neural activities of DRG neurons, EMG activities of selected muscles of the four limbs, and full-body locomotor kinematics will be recorded, and spindle afferent activities will be manipulated via optogenetic stimulation in selected DRGs during unconstrained cat locomotion. Machine learning (ML) models leveraging the spatiotemporal structures in the signals and mapping afferent activities in DRGs to limb kinematics will be applied for achieving closed-loop control of the optogenetic neuromodulation. The proposed research activities will be conducted by a team of collaborators with complementary research expertise in the areas of bioMEMS, wireless microelectronics, machine learning, artificial intelligence, and behavioral neuroscience. The successful development of the proposed intelligent and closed-loop optoelectronic neural interface will yield a robust building block for a comprehensive set of minimally invasive neural interfaces to study somatosensory control of movement, as well as monitor or treat somatosensory pathological conditions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.